As artificial intelligence reshapes industries across the board, a critical question echoes through law firms and corporate legal departments: will AI replace lawyers? For general counsel and their teams, the short answer is no. Probably not. The actual answer is far more nuanced than a simple yes or no, though, and understanding that nuance could determine who thrives in the profession’s next chapter.
The Reality Check: AI Won't Replace You, But AI-Savvy Lawyers Might
“We should not be worried about AI taking our jobs,” says Jasmine Singh, General Counsel at Ironclad, a company that makes AI-powered contract management tools, during a recent Axiom webinar on the human side of in-house counsel. Her perspective challenges the doom-and-gloom narrative surrounding AI and legal work.
And Singh's reasoning is grounded in practical reality: “AI for lawyers is best used when it is verified by someone who in fact understands and knows how the output should be used, what accurate and good output looks like.” Because the real threat isn't AI itself. It's complacency. As Singh puts it, channeling a now-familiar adage, “You won't be replaced by AI, you will be replaced by people that know how to use AI.”
Jonathan Fennell, General Counsel for ND Alliance Solutions, a medical management firm, echoes this sentiment from a different perspective. Even for companies not yet using AI, “there is always the potential,” he notes. “We're always looking at AI solutions as options for otherwise more mundane historic business problems now.”
What AI Cannot Replace: The Human Edge
When asked what percentage of day-to-day legal work could be automated by AI in the next five years, the majority of webinar attendees suggested between 10-50% could be automated, which is significant, but far from total replacement. This aligns with the irreplaceable human elements of legal practice both Singh and Fennell emphasize.
“In order to be able to evaluate the quality of output, you've got to be a quality lawyer,” Singh explains. “You have to have curiosity, you have to know which questions to ask, when to ask them, and you've got [to have] good judgment.”
In order to be able to evaluate the quality of output, you've got to be a quality lawyer.
That judgment requires something AI fundamentally lacks: contextual understanding. As a lawyer, you need to know how to apply facts to certain circumstances, understand the business environment you're working in, and grasp your company's risk profile. “These are all things that AI can't know,” Singh notes.
Fennell takes this further, identifying the core human skills that define effective legal counsel: “It can't provide the context. It can't provide the background. It can evaluate the quality of the product that it's giving you.”
Think about what truly makes legal professionals valuable. It's not just cranking out documents; it's relationships, emotional intelligence, lived experience, and the ability to counsel clients through crises. “It's lawyers, not necessarily as lawyers, but [us acting] as counselors and advisers,” Fennell observes.
AI advancements are empowering legal teams to bring strategic work back in-house.
The Communication Imperative
Recent research reveals that a striking 71% of general counsel feel they need to improve their communication with the business. Why is this such a persistent challenge, and what does it have to do with AI?
Communication, Singh explains, is the mechanism legal teams use to demonstrate not just the work they're doing but the impact of that work. “There's been a real shift over the last ten or so years where we hear legal teams being described as strategic thought partners, empowerers of the business, drivers of value, not just minimizers of risk,” she notes.
There's been a real shift over the last ten or so years where we hear legal teams being described as strategic thought partners, empowerers of the business, drivers of value, not just minimizers of risk.
This reframing demands that legal professionals speak the business's language. That means tracking legal work through data analytics and metrics, offering insights into how data drives decisions, and ensuring advice can actually be digested, heard, and acted upon.
“If we don't communicate in a way that makes it easy for our clients to do that, that's feedback for us that we need to improve,” Singh says. “Because otherwise, we can't actually help the business help itself.”
Fennell adds a crucial dimension: every interaction with the business is an opportunity to establish trust and rapport. When someone comes to in-house counsel, they might be aware they need legal attention, or they might begrudgingly check a box on a compliance checklist. Not only understanding what brings them to you but demonstrating competence and commitment to their success matters enormously.
“What we say needs to be relevant,” Fennell emphasizes. “Citing case of Smith v Johnson, you know, and how it shepherdizes out and whatnot is going to be irrelevant for most business leaders. They just simply want to know what's your advice.”
The Business Language Barrier
In industries like technology and healthcare, professionals pride themselves on experience in their domains. Doctors and tech innovators don't want to be told “no” by someone who doesn't understand the complexities of their work. This creates a delicate balance for legal professionals.
“You have to understand the language of business. You have to understand the objectives. You have to understand how people work,” Singh explains. “And then you have to understand what your company is building, delivering, servicing.”
You have to understand the language of business. You have to understand the objectives. You have to understand how people work, and then you have to understand what your company is building, delivering, servicing.
This understanding allows lawyers to show they're “in the shoes right next to them,” committed to helping partners achieve their goals. Building trust means showing where you don't know what you don't know. “I think those things also have helped me anyway get trust and buy-in from my partners,” Singh reflects.
Fennell underscores the importance of humility and subject matter experience: “The last thing you want is [a] ‘because I said so’ situation. It's understanding what does the business do, what's driving this individual, what are the motivations, what are their fears, what are their concerns, and how am I here to help them with whatever that specific thing is?”
GCs must speak the business's language, demonstrate business acumen, and act as trusted advisors—not just legal technicians.
AI's Impact on the Attorney-Client Relationship
Here's where AI enters the relationship equation in unexpected ways. Singh recounts a telling scenario: “I definitely have had counterparts say to me, like, oh, I did some legal research, and I found out that the answer was ‘blah’. What they did is they went to ChatGPT, and they asked some questions, and they got an answer that was not right.”
This phenomenon creates a critical teaching moment. Rather than viewing such interactions as threats to professional authority, effective in-house counsel must understand the motivation behind them. Was the person simply eager to move quickly? Were they genuinely curious and wanted to be prepared?
“What we might misdescribe as motivation will negatively influence the interaction from there,” Singh explains. One lawyer might perceive the ChatGPT research as disrespect, coming from “a place of frustration in that the next phase of that relationship.” But extending goodwill and trust leads to a different approach: partnering with that person to provide a complete picture of the law and how their circumstances might differ from ChatGPT's generic answer.
Fennell adds a lawyer's natural skepticism to the mix: “One thing law does really well or at least it did with me was it made me cynical of what people are proffering as proof or proffering as expertise.” This healthy skepticism, looking for indicators that information is reliable, accurate, and properly applied, becomes even more critical in the age of AI-generated legal information.
“When something tells us exactly what it we wanted to tell us, at least I'm always a little bit leery of that,” Fennell notes. “Why is this telling me what I want to hear? Is because it's what I want to hear, or is it because it's accurate?”
From Advisory to Actionable: Creating Real Business Value
Moving beyond being a legal “no person” requires making advice actionable, not just advisory. Singh provides a concrete example: When the law requires acknowledging terms in a product, you could simply tell the product team to make it happen. Or you could offer three different implementation options, explaining the risks and rewards of each approach.
“You empower your teams to actually say, ‘oh, these ones are technically infeasible. So, like, thanks for the suggestion, but we can't build it that way because we've got these limitations’,” Singh explains. This partnership approach transforms the legal function from obstacle to enabler.
The same principle applies to compliance requirements. When new California employer training obligations emerge, legal shouldn't just announce, “there's this new training required… go do it.” Instead, outline the required elements, offer to review content to ensure compliance, and partner with the people team throughout implementation.
Lawyers are problem solvers by nature.
“Lawyers are problem solvers by nature. We're problem identifiers and solvers,” Singh notes. But there's a caveat: “I think we always also have to be careful not to wade too much into to the waters of, like, ‘oh, here's what you should do, and I'm gonna go do it for you’.” This balance between providing actionable guidance and overstepping into business operations is what distinguishes effective in-house counsel who understand how to practice law within a corporate structure.
Establishing Yourself as a Trusted Partner
When Fennell moved between industries, from nonprofit and education into medical management, he faced the classic challenge of establishing credibility when you haven't worked in a specific field previously.
His approach centers on genuine curiosity: “Help me understand what you do on a day-to-day basis.”
“Sometimes we flag the problems,” Fennell explains. “Again, if we look at, like, process mapping, process improvement projects, things like that, but it's not on us to go and solve the problem. It's about facilitating discussions and conversations.”
A couple of the best questions to ask when joining a company? “What frustrates you? What bottlenecks do you experience?” This creates an environment where feedback is welcome, not mean-spirited criticism, but aimed at improving products, services, and processes.
How In-House Counsel Are Actually Using AI
When discussion turns to practical applications, Singh identifies three distinct modes of AI usage among in-house legal teams:
The Intern Mode: This covers routine, manual work that lawyers want off their plates. Examples include redlining contracts against playbooks, identifying risks against risk matrices, summarizing redlines, fixing clerical errors, or creating first-pass documents. For legal professionals engaged in high-volume document review, AI tools can dramatically accelerate the process while maintaining quality standards.
The Thought Partner Mode: Here, AI helps lawyers explore unfamiliar territory. When an engineering partner wants to use a new tool that involves disclosing code, you might ask AI: “What questions would you ask back in order to understand the risk associated with this new usage?” This supercharges issue-spotting abilities and helps lawyers ask informed questions rather than scrambling to understand basic concepts.
The Sparring Partner Mode: This involves using AI to identify holes in your work. Before sending a message to executives about compliance requirements, ask AI what pushback you might get and how to address counter-arguments. Before a contract negotiation, explore what positions the other side might take and how to craft your responses.
“I think there are buckets of use cases within each that really run the gambit of all different types of practice areas,” Singh notes. In contract work specifically, AI excels at contract analysis, redlining agreements using your playbook or precedent, generating summaries of changes, drafting explanatory emails to opposing counsel, and helping prepare for negotiations by anticipating counterparty positions.
The goal, Singh emphasizes, isn't just efficiency. It's making work “a little bit more humane and fun” while achieving better outputs for clients.
Where AI Falls Short
For all its promise, AI has significant limitations that in-house counsel must understand. Fennell identifies a fundamental challenge: “Understanding the tool. It might sound unsophisticated, but I think it's really not understanding the potential of the tool.”
Even sophisticated legal professionals may not know how to effectively employ AI for their specific needs. This creates a need for environments where legal teams have “the freedom, should I say, dare I say, to play around, to fail, to risk, to be creative with it as a tool.”
But there's a paradox here. “As lawyers, we can sort of pride ourselves on being right. Like, our job demands that we're right,” Fennell notes. “So here we find ourselves with a tool that we are, we have to play with to get better at it.”
Singh adds two critical limitations. First, AI is dangerous when you don't know what the output should look like: “If you're doing legal research in a publicly available AI tool that maybe doesn't have the actual law at its fingertips or access to the case law, and it might be hallucinating or it might be citing the wrong thing or it might be summarizing a Reddit thread about the law, which is inaccurate, and you don't have a Westlaw license or whatever it is that you need to go vet the accuracy of that output, that is not an ideal use case of AI for you.” This is particularly concerning as generative AI becomes more sophisticated at producing plausible-sounding but potentially incorrect legal analysis.
Second, lawyers must observe their duties around confidentiality and privilege. “It's just being really careful to make sure that we're not using public facing tools that are training on our data in a way that is prohibited by our organization's data security protections or policies or governance policies.”
The solution? Understanding which tools to use for which queries and which data, ensuring you have the right enterprise licenses, and that “no train, no retain” settings are enabled where necessary.
The Verification Imperative
“Accuracy is a nonnegotiable,” Fennell states firmly. “Fast is not going to be good if the output is wrong.”
Accuracy is a nonnegotiable.
This principle extends to every aspect of AI use in legal practice. When AI provides an output, lawyers cannot simply trust it because it sounds authoritative. “If you use a tool and it gives us an output, we don't know how it got that output, we have no way to verify or confirm that the output is in fact accurate, pause,” Fennell advises.
Even something as basic as party identification in contracts matters. “I've seen contracts where they've got the wrong parties listed,” Fennell notes. “And, you know, you can analyze all the terms and conditions and material provisions in the contract, but you've missed on something as simple as who's the party to this.”
Singh acknowledges that verification requires lawyers who genuinely understand their field: “I don't really use AI to do complicated math because if I don't know the ability to check that that math was right, I'm not just going to be like, ‘okay. Whatever AI said’.”
The same logic applies to legal research. Using AI without the ability to verify citations, scrutinize legal reasoning, identify potential biases, and evaluate argument completeness creates unacceptable risk.
The Value Proposition for Smaller Legal Teams
For lean, in-house legal departments, AI offers particular promise. As Fennell notes from his experience, lawyers are “doing so much with not a ton of resources all the time.”
Research from Ironclad's study on AI and legal work revealed a surprising benefit: 76% of respondents said AI helped with their burnout, supporting during challenging moments.
“I know especially in house, all of us are doing so much with not a ton of resources all the time,” Singh reflects. “Having AI as just somebody to help you, I know it's something, but sometimes it feels like somebody else to be your partner in these moments when you're like, ‘I just wish I had somebody else to help me think this problem.’ Or like, ‘Man, staring at a blank page is really hard. I just wish I had somewhere to start from’.”
This perspective reframes AI as a collaborative tool, making practice “slightly more fun and a little bit more humane and a little bit more collaborative and enjoyable.”
90% of in-house teams face pressure to improve efficiency—AI helps lawyers do more with less.
The Skills That Matter Most
When webinar attendees were asked which skill would be most valuable for in-house counsel to improve in the next three years, business acumen topped the list, followed by project management, with legal expertise and AI fluency tied for third.
This ranking reveals professional priorities: understanding the business, managing complex initiatives, and then balancing traditional legal knowledge with technological fluency. It's a hierarchy that makes sense given everything Singh and Fennell discussed about the evolving role of in-house counsel.
“Legal happens to be one of the biggest adopters of AI technology,” Singh notes. “In this moment, right, year over year, our use cases continue to expound.” But adoption must be thoughtful, not reflexive.
Legal professionals sit at a unique intersection: They're both gatekeepers of AI technology their organizations can use and super users of AI themselves. This creates dual responsibilities –advising on responsible AI procurement and implementation while leveraging AI tools effectively in their own work.
The consensus from both panelists is clear: AI will transform legal work, but it won't eliminate the need for human lawyers. What it will do is separate those who adapt from those who don't.
“I think it's to really augment lawyers. I think it's to help us free up our time, to sort of outsource some of the road work, some of the repeat tasks, tell free us up to do some of the more strategic work,” Singh envisions. “I also think it's to up-level us. It's really enabling us to make sure that our work product is as good as it could possibly be.”
That means work that's clear, understandable, preempts questions, provides optionality, and serves business needs effectively. AI becomes a tool for making legal practice not just faster but better, more strategic, more collaborative, more valuable to the organizations lawyers serve.
The lawyers who thrive will be the ones who understand how to blend technological capability with human judgment, business acumen with legal experience, and efficiency with empathy. They'll be the ones who remember that while AI can process contracts, only humans can truly counsel clients through the complex, ambiguous, emotionally charged situations where legal experience matters most.